Robust Bidding Strategy and Profit Allocation for Cooperative DSR Aggregators With Correlated Wind Power Generation

• Published in: IEEE transactions on sustainable energy Vol. 10; no. 4; pp. 1904 - 1915
• Main Authors: Li, Bosong, Wang, Xu, Shahidehpour, Mohammad, Jiang, Chuanwen, Li, Zhiyi
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Ancillary services; Aumann–Shapely procedure; Correlation; Demand side management; DSR aggregators with correlated wind power generation; Electric power generation; Electric vehicle charging; Electricity consumption; Feasibility studies; Implantation; Lagrange multiplier; Markets; Mixed integer; optimal payoff allocation; Optimization; Resource management; robust cooperative bidding strategy; Strategy; Uncertainty; Wind power; Wind power generation
• ISSN: 1949-3029; 1949-3037
• DOI: 10.1109/TSTE.2018.2875483

Aggregation is an effective way of collective management of demand-side resources (DSRs). As an independent entity in electricity market, DSR aggregator can participate in both the energy and ancillary services markets. The DSR aggregator's optimal bidding strategy is subject to market price uncertainties and resource variability. In this paper, spatial correlation of wind power generation is considered in developing a robust DSR bidding strategy which takes into account individual and cooperative aggregators. The proposed model is transformed into and solved as a mixed integer second order cone programming (MISOCP) problem. The Aumann-Shapley procedure is applied in this paper to allocate the payoff among cooperative DSR aggregators considering potential uncertainties. By replacing binary variables with their optimal values, the original MISOCP is transformed into a second order cone programming (SOCP) problem and Lagrange multipliers are employed for the implantation of a discrete Aumann-Shapley procedure. Case studies verify the feasibility and effectiveness of the proposed bidding model and payoff allocation procedure.